Mean field evolutionary dynamics in dense-user multi-access edge computing systems

Hao Gao, Wuchen Li, Reginald A. Banez, Zhu Han, H. Vincent Poor

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Multi-access edge computing (MEC) can use the distributed computing resources to serve the large numbers of mobile users in the next generation of communication systems. In this new architecture, a limited number of mobile edge servers will serve a relatively large number of mobile users. Heterogeneous servers can provide either single resource or multiple different resources to the massive number of selfish mobile users. To achieve high quality of service (QoS) and low latency under these two cases, we construct two system models and formulate our problems as two non-cooperative population games. Then we apply our proposed mean field evolutionary approach with two different strategy graphs to solve the load balancing problems under those two cases. Finally, to evaluate the performance of our algorithms, we employ the following performance indicators: Overall response time (average response time of the whole system), individual response time (response time of each server), and fairness index (equality of users' response time).

Original languageEnglish (US)
Article number3016695
Pages (from-to)7825-7835
Number of pages11
JournalIEEE Transactions on Wireless Communications
Volume19
Issue number12
DOIs
StatePublished - Dec 2020

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Applied Mathematics

Keywords

  • MEC
  • Mean field evolutionary approach
  • dense-user
  • load balancing

Fingerprint

Dive into the research topics of 'Mean field evolutionary dynamics in dense-user multi-access edge computing systems'. Together they form a unique fingerprint.

Cite this